Robot Workspace Point-Cloud Filtering for Interference Avoidance
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Solution Overview
Problem
Existing methods for specifying the interference region around industrial robots are inaccurate due to color differentiation issues between the robot and workpieces, which are exacerbated by stains, color changes, and lighting variations, leading to potential interference misidentification.
Innovation Solution
A terminal device that sets a user coordinate system based on a marker in the image, uses point-group data to specify the robot region, and creates interference avoidance data by removing robot-related point-group data from the overall point-group data, allowing for precise identification of the interference region and enabling the robot to perform tasks while avoiding obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If color-based interference region setting is used, then the robot can avoid interference with objects, but the accuracy of specifying the interference region deteriorates due to color differentiation issues
Solution Approach 1:
A marker is introduced as an intermediary object attached to the robot. The marker serves as a reliable reference that is distinct from workpieces and environment, enabling accurate coordinate system establishment without relying on color differentiation between the robot and surrounding objects.
Solution Approach 2:
The patent replaces the optical/color-based detection system with a coordinate geometry-based system. Instead of using color cameras and image processing to distinguish the robot from objects, the system uses a marker-based coordinate framework combined with distance measuring devices to precisely define the interference region through spatial relationships.
2Ease of manufacture
If color differentiation is used to identify the robot, then the interference region can be set, but the reliability deteriorates due to stains, color changes, and lighting variations
Solution Approach 1:
The marker attached to the robot acts as a stable intermediary reference that is not affected by environmental factors. This marker provides consistent, reliable identification and positioning information regardless of lighting conditions, stains, or color changes in the robot's body or work environment.
Solution Approach 2:
The system changes the detection parameter from color-based identification to coordinate-based identification using a marker. This parameter change makes the robot identification process independent of lighting conditions and color variations, significantly improving reliability in diverse environmental conditions.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution significantly improves the accuracy of specifying the interference region, enabling the industrial robot to perform tasks while avoiding interference with other objects, even when color differentiation is challenging, by using a marker-based coordinate system and point-group data processing.
Implementation Method 1
a distance measuring portion (15) which measures a distance to an object included in the image
Data Source
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AI summary
A terminal device includes a coordinate-system setting portion which sets a user coordinate system on the basis of a marker included in an image, photographed by a photographing portion, including an industrial robot and a work space of the industrial robot, a coordinate giving portion which gives a coordinate of the user coordinate system to point-group data obtained by a distance measuring portion which measures a distance to an object included in the image, a region specifying portion which specifies a robot region on the user coordinate system corresponding to the industrial robot on the basis of shape size information of the industrial robot corresponding to a type of the industrial robot and attitude information of the industrial robot, and a point-group creating portion for avoidance which creates point-group data for interference avoidance by removing the point-group data included in the robot region from the point-group data obtained by the distance measuring portion.